Vehicle-provided recommendations for use of adas systems

ABSTRACT

Systems and methods are provided for an advanced driver-assistance system (ADAS) that obtains data from a plurality of sensors. In some embodiments, the system can retrieve data regarding a user’s past interactions and analyze the data with the sensor data to determine the user’s behavior. In some embodiments, the ADAS can determine whether a user is unaware of an ADAS feature based on this behavior and a prompt that recommends the ADAS feature. The user’s response to this prompt may be incorporated into the user’s behavior for future recommendations.

TECHNICAL FIELD

The present disclosure relates generally to autonomous driving, and inparticular, some implementations may relate to driving systems thatevaluate driver conditions and behaviors to predict optimal autonomousdriving.

DESCRIPTION OF RELATED ART

Advanced driver-assistance systems (ADAS) can refer to electronicsystems that assist a vehicle operator while driving, parking, orotherwise maneuvering a vehicle. ADAS can increase vehicle and roadsafety by minimizing human error, and introducing some level ofautomated vehicle/vehicle feature control. Fully autonomous drivingsystems may go further than ADAS by leaving responsibility ofmaneuvering and controlling a vehicle to the autonomous driving systems.For example, an autonomous driving system may comprise some package orcombination of sensors to perceive a vehicle’s surroundings, advancedcontrol systems that interpret the sensory information to identifyappropriate navigation paths, obstacles, road signage, etc., and controlthe vehicle to effectuate movement in accordance with the appropriatenavigation paths.

BRIEF SUMMARY OF THE DISCLOSURE

In accordance with one embodiment, a method for effectuating an advanceddriver-assistance system (ADAS) of a vehicle may comprise obtainingsensor data from a plurality of sensors; retrieving data on a user’spast interactions with the ADAS; determining the user’s behavior basedon the sensor data and data on past user interactions; and adjusting theADAS in response to the user’s behavior.

In some embodiments, the method further comprises determining whetherthe user is unaware of the existence of an ADAS feature based on theuser’s behavior and recommending the ADAS feature to the user if theuser is determined to be aware.

In some embodiments, adjusting the ADAS comprises determining whether anADAS feature is applicable to a situation and recommending the ADASfeature to the user.

In some embodiments, the data on the user’s past interactions includesinformation of each of turn on operations of the ADAS and turn offoperations of the ADAS.

In some embodiments, recommending the ADAS feature includes providing aprompt to initiate the ADAS feature and initiating the ADAS feature.

In some embodiments, providing the prompt is completed with a LEDdisplay and the LED display provides a shortcut to turn on therecommended ADAS feature.

In some embodiments, the method further comprises determining when theuser turned off an ADAS feature; determining whether the ADAS featurewas subsequently updated; and notifying the user about the updated ADASfeature.

In some embodiments, determining the user’s behavior involves a firstuser, and further comprises sharing the user behavior with a seconduser.

In some embodiments, the sensor data includes the user’s facial andphysical expressions.

In some embodiments, the past user interaction data includes previousrecommendations on ADAS features that the user ignored.

In some embodiments, the past user interaction data includes the numberof times an ADAS feature was turned off.

In accordance with another embodiment, a vehicle may comprise aprocessor; a plurality of sensors, and a memory unit operativelyconnected to the processor and including computer code, that whenexecuted, causes the processor to obtain sensor data from the pluralityof sensors; retrieve data on a user’s past interactions with an ADASmodule; determine the user’s behavior based on the sensor data and dataon past user interactions; determine whether the user is unaware of anADAS feature; recommend the ADAS feature to the user on a display bypresenting, on the display, a prompt to initiate the ADAS feature; andadjust the ADAS in response to the user’s behavior.

In some embodiments, the prompt is a textual message and furthercomprises an actuation mechanism to initiate the ADAS feature and anactuation mechanism to ignore the prompt

In some embodiments, the memory unit includes computer code, that whenexecuted, further causes the processor to determine whether an ADASfeature is applicable to a situation.

In some embodiments, the data on the user’s past interactions includesinformation of each of turn on operations of the ADAS and turn offoperations of the ADAS.

In some embodiments, the user’s behavior reflects the past interactionsof a first user, and the memory unit includes computer code, that whenexecuted, further causes the processor to share the user behavior with asecond user.

In some embodiments, the past user interaction data includes previousrecommendations on ADAS features that the user ignored, and the memoryunit includes computer code, that when executed, further causes theprocessor to abstain from recommending an ADAS feature if the userpreviously ignored a recommendation.

In some embodiments, the past user interaction data includes the numberof times an ADAS feature was turned off and wherein the memory unitincludes computer code, that when executed, further causes the processorto abstain from recommending an ADAS feature if the ADAS feature wasturned off one or more times.

In some embodiments, the one or more sensors includes at least one of aneye tracking sensor, speed sensor, facial recognition sensor, andenvironmental sensor.

In some embodiments, the vehicle further comprises an LED display.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure, in accordance with one or more variousembodiments, is described in detail with reference to the followingfigures. The figures are provided for purposes of illustration only andmerely depict typical or example embodiments.

FIG. 1 is a schematic representation of an example vehicle with whichembodiments of the systems and methods disclosed herein may beimplemented.

FIG. 2A illustrates an example autonomous control system.

FIG. 2B illustrates an example safety control unit aspect of theautonomous control system of FIG. 2A.

FIG. 3 illustrates an example recommendation made to a driver inaccordance with various embodiments.

FIG. 4 is a flow chart illustrating operations that may be performed toeffectuate influential control in accordance with one embodiment.

FIG. 5 is an example computing component that may be used to implementvarious features of embodiments described in the present disclosure.

DETAILED DESCRIPTION

As alluded to above, ADAS and autonomous driving control systems can beused in vehicles that at least, in part, control or manage vehicleoperation to provide varying levels of automated control or assistance,and may or may not actually influence/affect driving dynamics. For easeof reference, the term “autonomous control” will be used herein to referto such systems. In some vehicles, an override mechanism, such as anoverride switch, may be used to turn off or disengage a vehicle’sautonomous control system. Such an override mechanism can allow adriver/operator or passenger to assume manual control of a vehicle. Wheninvoking conventional implementations of override mechanisms in a safetyscenario (e.g., to avoid a collision), a vehicle operator engages in ahuman/manual situational assessment, and may intervene/overrideautonomous control by manually actuating a driving control mechanism,such as grasping and controlling a steering wheel, actuating a brakepedal, actuating a throttle pedal, and so on. In some vehicles, ADASprovide warning alerts or notifications to a driver, where thesealerts/notifications are intended to invoke some reaction or responsefrom the driver to, e.g., correct a current driving behavior.

It should be understood that the current (and a least a portion of afuture) state of vehicular autonomous control may fall under what can bereferred to as a transition period prior to the realization of fullyautonomous driving. Thus, a human operator, i.e., a driver of a vehicle,may still inject some amount of control and/or may be prompted to takecertain action(s), e.g., in response to some road or vehicle operatingcondition as alluded to above. In particular, such influential controlmay act as an intuitive reinforcement of some action(s) beingpromulgated by a vehicle ADAS, e.g., so that the driver of the vehiclemay understand and appreciate the autonomous control being effectuatedover the vehicle. In some embodiments, such influential control,alternatively, or in addition to the aforementioned reinforcement, mayact to induce or prompt the driver to impart some complementaryaction(s) to existing ADAS-initiated control of the vehicle, or even inresponse to current driver-initiated control of the vehicle. In theevent the driver’s current action(s) do not comport withADAS-effectuated control (or if the driver’s current action(s) should beenhanced or augmented with additional action(s)/greater level ofaction(s)), such influential control can make the driver aware thathis/her action(s) differ from the ADAS-effectuated control and/orintervene to induce or prompt the driver to stop his/her non-conformingaction(s)/behavior(s).

In some current ADASs, a torque may be applied, by/under the control ofthe ADAS system, to the steering wheel so that actual steering can beinfluenced. That is, in some scenarios, the actual driving dynamics of avehicle can be affected by this ADAS feature.

In contrast, some embodiments of the present disclosure do not directlyinfluence the driving dynamics of a vehicle. Rather, some embodimentsresult in providing a recommendation that the driver understands, butone that the driver can choose to ignore if desired. Embodiments can beespecially helpful in situations where an ADAS may make a recommendationfor an action to be undertaken by the driver, but the ADAS may not bevery confident with the recommendation. Moreover, use of variousembodiments avoids driver skill degradation/degeneration. That is,because some embodiments provide recommendations/influentialcues/control only, the driver is not actually relieved frommanual/mechanical control, and the driver’s driving skills can bemaintained rather than lost (as might be the case over time/with fullyautonomous vehicles). For example, a prompt may appear on a displayasking if a driver would like to initiate cruise control. If the driveris in a high traffic area, cruise control may not be optimal as a hightraffic area does not allow for a consistent speed, so the driver maychoose to ignore the prompt. By using a display with a shortcut to theADAS feature, the driver still maintains full control and initiates anyADAS features.

As further described below, some embodiments provide recommendationsbased on the past and current actions of the driver. Some embodimentscan develop a driver profile that includes the driver’s characteristicsand tendencies while driving. This profile fuels recommendations made tothe driver and may evolve over time, and in some embodiments, thatevolution may constantly occur. As the driver completes more trips, theprofile can be updated to reflect more accurate characteristics. Thesystem may also take into account how the driver reacts torecommendations and prompts. A successful prompt, i.e. wherein the useraccepts the prompt to initiate the recommended ADAS feature, can trainthe system to accurately determine when a recommendation is appropriateand likely successful. The system can build upon the commoncharacteristics of previous drivers as a starting point, and narrow itsscope upon further experience with a particular driver. This system canbe individually implemented for multiple drivers that use the vehicle.In that case, the system will maintain separate profiles and can trainseparate models for each driver.

The systems and methods disclosed herein may be implemented with or byany of a number of different vehicles and vehicle types. For example,the systems and methods disclosed herein may be used with automobiles,trucks, motorcycles, recreational vehicles and other like on-or off-roadvehicles. In addition, the principles disclosed herein may also extendto other vehicle types as well. An example hybrid electric vehicle isillustrated and described below as one example.

FIG. 1 illustrates an example hybrid electric vehicle (HEV) 100 in whichvarious embodiments for driver disengagement of autonomousvehicle/driving controls may be implemented. It should be understoodthat various embodiments disclosed herein may be applicable to/used invarious vehicles (internal combustion engine (ICE) vehicles, fullyelectric vehicles (EVs), etc.) that are fully or partially autonomouslycontrolled/operated, not only HEVs.

HEV 100 can include drive force unit 105 and wheels 170. Drive forceunit 105 may include an engine 110, motor generators (MGs) 191 and 192,a battery 195, an inverter 197, a brake pedal 130, a brake pedal sensor140, a transmission 120, a memory 160, an electronic control unit (ECU)150, a shifter 180, a speed sensor 182, and an accelerometer 184.

Engine 110 primarily drives the wheels 170. Engine 110 can be an ICEthat combusts fuel, such as gasoline, ethanol, diesel, biofuel, or othertypes of fuels which are suitable for combustion. The torque output byengine 110 is received by the transmission 120. MGs 191 and 192 can alsooutput torque to the transmission 120. Engine 110 and MGs 191 and 192may be coupled through a planetary gear (not shown in FIG. 1B). Thetransmission 120 delivers an applied torque to the wheels 170. Thetorque output by engine 110 does not directly translate into the appliedtorque to the wheels 170.

MGs 191 and 192 can serve as motors which output torque in a drive mode,and can serve as generators to recharge the battery 195 in aregeneration mode. The electric power delivered from or to MGs 191 and192 passes through inverter 197 to battery 195. Brake pedal sensor 140can detect pressure applied to brake pedal 130, which may further affectthe applied torque to wheels 170. Speed sensor 182 is connected to anoutput shaft of transmission 120 to detect a speed input which isconverted into a vehicle speed by ECU 150. Accelerometer 184 isconnected to the body of HEV 100 to detect the actual deceleration ofHEV 100, which corresponds to a deceleration torque.

Transmission 120 is a transmission suitable for an HEV. For example,transmission 120 can be an electronically controlled continuouslyvariable transmission (ECVT), which is coupled to engine 110 as well asto MGs 191 and 192. Transmission 120 can deliver torque output from acombination of engine 110 and MGs 191 and 192. The ECU 150 controls thetransmission 120, utilizing data stored in memory 160 to determine theapplied torque delivered to the wheels 170. For example, ECU 150 maydetermine that at a certain vehicle speed, engine 110 should provide afraction of the applied torque to the wheels while MG 191 provides mostof the applied torque. ECU 150 and transmission 120 can control anengine speed (NE) of engine 110 independently of the vehicle speed (V).

ECU 150 may include circuitry to control the above aspects of vehicleoperation. ECU 150 may include, for example, a microcomputer thatincludes one or more processing units (e.g., microprocessors), memorystorage (e.g., RAM, ROM, etc.), and I/O devices. ECU 150 may executeinstructions stored in memory to control one or more electrical systemsor subsystems in the vehicle. ECU 150 can include a plurality ofelectronic control units such as, for example, an electronic enginecontrol module, a powertrain control module, a transmission controlmodule, a suspension control module, a body control module, and so on.As a further example, electronic control units can be included tocontrol systems and functions such as doors and door locking, lighting,human-machine interfaces, cruise control, telematics, braking systems(e.g., anti-lock braking system (ABS) or electronic stability control(ESC)), battery management systems, and so on. These various controlunits can be implemented using two or more separate electronic controlunits, or using a single electronic control unit.

MGs 191 and 192 each may be a permanent magnet type synchronous motorincluding for example, a rotor with a permanent magnet embedded therein.MGs 191 and 192 may each be driven by an inverter controlled by acontrol signal from ECU 150 so as to convert direct current (DC) powerfrom battery 195 to alternating current (AC) power, and supply the ACpower to MGs 191, 192. MG 192 may be driven by electric power generatedby motor generator MG191. It should be understood that in embodimentswhere MG191 and MG192 are DC motors, no inverter is required. Theinverter, in conjunction with a converter assembly may also accept powerfrom one or more of MGs 191, 192 (e.g., during engine charging), convertthis power from AC back to DC, and use this power to charge battery 195(hence the name, motor generator). ECU 150 may control the inverter,adjust driving current supplied to MG 192, and adjust the currentreceived from MG191 during regenerative coasting and braking.

Battery 195 may be implemented as one or more batteries or other powerstorage devices including, for example, lead-acid batteries, lithiumion, and nickel batteries, capacitive storage devices, and so on.Battery 195 may also be charged by one or more of MGs 191, 192, such as,for example, by regenerative braking or by coasting during which one ormore of MGs 191, 192 operates as generator. Alternatively (oradditionally, battery 195 can be charged by MG 191, for example, whenHEV 100 is in idle (not moving/not in drive). Further still, battery 195may be charged by a battery charger (not shown) that receives energyfrom engine 110. The battery charger may be switched or otherwisecontrolled to engage/disengage it with battery 195. For example, analternator or generator may be coupled directly or indirectly to a driveshaft of engine 110 to generate an electrical current as a result of theoperation of engine 110. Still other embodiments contemplate the use ofone or more additional motor generators to power the rear wheels of avehicle (e.g., in vehicles equipped with 4-Wheel Drive), or using tworear motor generators, each powering a rear wheel.

Battery 195 may also be used to power other electrical or electronicsystems in the vehicle. Battery 195 can include, for example, one ormore batteries, capacitive storage units, or other storage reservoirssuitable for storing electrical energy that can be used to power MG 191and/or MG 192. When battery 195 is implemented using one or morebatteries, the batteries can include, for example, nickel metal hydridebatteries, lithium ion batteries, lead acid batteries, nickel cadmiumbatteries, lithium ion polymer batteries, and other types of batteries.

FIG. 2A illustrates an example autonomous control system 200 that may beused to autonomously control a vehicle, e.g., HEV 100. Autonomouscontrol system 200 may be installed in HEV 100, and executes autonomouscontrol of HEV 100. As described herein, autonomous control can refer tocontrol that executes driving/assistive driving operations such asacceleration, deceleration, and/or steering of a vehicle, generalmovement of the vehicle, without necessarily depending or relying ondriving operations/directions by a driver or operator of the vehicle.

As an example, autonomous control may include lane keeping assistcontrol where a steering wheel (not shown) is steered automatically(namely, without depending on a steering operation by the driver) suchthat HEV 100 does not depart from a running lane. That is, the steeringwheel is automatically operated/controlled such that HEV 100 runs alongthe running lane, even when the driver does not perform any steeringoperation. As alluded to above, other autonomous control may includeassistive driving mechanisms in the form of, e.g., visual or audiblealerts or warnings, indirect haptic feedback, such as vibrating thedriver’s seat, etc.

As another example, autonomous control may include navigation control,where when there is no preceding vehicle in front of the HEV 100,constant speed (cruise) control is effectuated to make HEV 100 run at adetermined constant speed. When there is a preceding vehicle in front ofHEV 100, follow-up control is effectuated to adjust HEV 100′s speedaccording to a distance between HEV 100 and the preceding vehicle.

In some scenarios, switching from autonomous control to manual drivingmay be executed. Whether or not to execute this switch from autonomouscontrol to manual driving may be determined based on a comparisonbetween a comparison target and a threshold. In one embodiment, thecomparison target is quantified so as to be compared with the threshold.When the comparison target is equal to or more than the threshold, theautonomous control system 200 executes the switch from an autonomouscontrol mode to a manual driving mode. In other situations/scenarios,autonomous control system 200 may take over operation, effecting aswitch from manual driving/control to autonomous control. As will bediscussed in greater detail below, autonomous control system 200 maymake certain determinations regarding whether to comply or proceed withautonomous control based on a command from autonomous control system200. For example, considerations regarding recoverability and vehiclecontrol under certain conditions may be considered as factors indetermining whether or not autonomous control can be safely executed.Such considerations may also be reflected as thresholds for comparison.

For example, when an operation amount of any of a steering operation, anacceleration operation, and brake operation by the driver of HEV 100during the autonomous driving control becomes equal to or more than athreshold, autonomous control system 200 may execute a switch fromautonomous control to manual control.

It should be understood that manual control or manual driving can referto a vehicle operating status wherein a vehicle’s operation is basedmainly on driver-controlled operations/maneuvers. In an ADAS context,driving operation support control can be performed during manualdriving. For example, a driver may be actively performing any of asteering operation, an acceleration operation, and a brake operation ofthe vehicle, while autonomous control apparatus 200 performs some subsetof one or more of those operations, e.g., in an assistive,complementary, or corrective manner. As another example, drivingoperation support control adds or subtracts an operation amount to orfrom the operation amount of the manual driving (steering, acceleration,or deceleration) that is performed by the driver. It should beunderstood that in such scenarios, use of influential control over adriver’s steering hand(s), because a driver is already engaging in a“proper” operation, may enforce or positively reinforce the driver’saction(s).

In the example shown in FIG. 2A, autonomous control system 200 isprovided with an external sensor 201, a GPS (Global Positioning System)reception unit 202, an internal sensor 203, a map database 204, anavigation system 205, actuators 206, an HMI (Human Machine Interface)207, a monitor device 208, a shift lever 209, auxiliary devices 210.Autonomous control system 200 may communicate with ECU 150, or in someembodiments (may be implemented with its own ECU).

In the example shown in FIG. 2A, external sensor 201 is a detector thatdetects external circumstances such as surrounding information of HEV100. The external sensor 201 may include at least one of a camera, aradar, and a Laser Imaging Detection and Ranging (LIDAR) unit.

The camera unit may be an imaging device that images the externalcircumstances surrounding the vehicle. For example, the camera isprovided on a back side of a front windshield of the vehicle. The cameramay be a monocular camera or a stereo camera. The camera outputs, to theECU 150, image information on the external circumstances surrounding thevehicle. The camera is not limited to a visible light wavelength camerabut can be an infrared camera.

The radar unit uses radio waves to detect obstacles outside of thevehicle by transmitting radio waves to the surroundings of the vehicle,and receiving reflected radio waves from an obstacle to detect theobstacle, distance to the obstacle or a relative positional direction ofthe obstacle. The radar unit outputs detected obstacle information tothe ECU 150.

The LIDAR unit may operate similar to the manner in which the radar unitoperates except that light is used in place of radio waves. The LIDARunit outputs detected obstacle information to the ECU 150.

In the example shown in FIG. 2A, GPS reception unit 202 receives signalsfrom three or more GPS satellites to obtain position informationindicating a position of HEV 100. For example, the position informationcan include latitude information and longitude information. The GPSreception unit 202 outputs the measured position information of thevehicle to the ECU 150.

In the example shown in FIG. 2A, the internal sensor 203 is a detectorfor detecting information regarding, e.g., a running status of HEV 100,operational/operating conditions, e.g., amount of steering wheelactuation, rotation, angle, amount of acceleration, accelerator pedaldepression, brake operation by the driver of HEV 100. The internalsensor 203 includes at least one of a vehicle speed sensor, anacceleration sensor, and a yaw rate sensor. Moreover, internal sensor203 may include at least one of a steering sensor, an accelerator pedalsensor, and a brake pedal sensor.

A vehicle speed sensor is a detector that detects a speed of the HEV100. In some embodiments, HEV 100′s speed may be measured directly orthrough calculations/inference depending on the operatingconditions/status of one or more other components of HEV 100. Forexample, a wheel speed sensor can be used as the vehicle speed sensor todetect a rotational speed of the wheel, which can be outputted to ECU150.

The acceleration sensor can be a detector that detects an accelerationof the vehicle. For example, the acceleration sensor may include alongitudinal acceleration sensor for detecting a longitudinalacceleration of HEV 100, and a lateral acceleration sensor for detectinga lateral acceleration of HEV 100. The acceleration sensor outputs, tothe ECU 150, acceleration information.

The yaw rate sensor can be a detector that detects a yaw rate (rotationangular velocity) around a vertical axis passing through the center ofgravity of HEV 100. For example, a gyroscopic sensor is used as the yawrate sensor. The yaw rate sensor outputs, to the ECU 150, yaw rateinformation including the yaw rate of HEV 100.

The steering sensor may be a detector that detects an amount of asteering operation/actuation with respect to a steering wheel 30 by thedriver of HEV 100. The steering operation amount detected by thesteering sensor may be a steering angle of the steering wheel or asteering torque applied to the steering wheel, for example. The steeringsensor outputs, to the ECU 150, information including the steering angleof the steering wheel or the steering torque applied to the steeringwheel of HEV 100.

The accelerator pedal sensor may be a detector that detects a strokeamount of an accelerator pedal, for example, a pedal position of theaccelerator pedal with respect to a reference position. The referenceposition may be a fixed position or a variable position depending on adetermined parameter. The accelerator pedal sensor is provided to ashaft portion of the accelerator pedal AP of the vehicle, for example.The accelerator pedal sensor outputs, to the ECU 150, operationinformation reflecting the stroke amount of the accelerator pedal.

The brake pedal sensor may be a detector that detects a stroke amount ofa brake pedal, for example, a pedal position of the brake pedal withrespect to a reference position. Like the accelerator position, a brakepedal reference position may be a fixed position or a variable positiondepending on a determined parameter. The brake pedal sensor may detectan operation force of the brake pedal (e.g. force on the brake pedal,oil pressure of a master cylinder, and so on). The brake pedal sensoroutputs, to the ECU 150, operation information reflecting the strokeamount or the operation force of the brake pedal.

A map database 204 may be a database including map information. The mapdatabase 204 is implemented, for example, in a disk drive or othermemory installed in HEV 100. The map information may include roadposition information, road shape information, intersection positioninformation, and fork position information, for example. The road shapeinformation may include information regarding a road type such as acurve and a straight line, and a curvature angle of the curve. Whenautonomous control system 200 uses a Simultaneous Localization andMapping (SLAM) technology or position information of blocking structuralobjects such as buildings and walls, the map information may furtherinclude an output signal from external sensor 201. In some embodiments,map database 204 may be a remote data base or repository with which HEV100 communicates.

Navigation system 205 may be a component or series of interoperatingcomponents that guides the driver of HEV 100 to a destination on a mapdesignated by the driver of HEV 100. For example, navigation system 205may calculate a route followed or to be followed by HEV 100, based onthe position information of HEV 100 measured by GPS reception unit 202and map information of map database 204. The route may indicate arunning lane of a section(s) of roadway in which HEV 100 traverses, forexample. Navigation system 205 calculates a target route from thecurrent position of HEV 100 to the destination, and notifies the driverof the target route through a display, e.g., a display of a head unit,HMI 207 (described below),, and/or via audio through a speaker(s) forexample. The navigation system 205 outputs, to the ECU 150, informationof the target route for HEV 100. In some embodiments, navigation system205 may use information stored in a remote database, like map database204, and/or some information processing center with which HEV 100 cancommunicate. A part of the processing executed by the navigation system205 may be executed remotely as well.

Actuators 206 may be devices that execute running controls of HEV 100.The actuators 206 may include, for example, a throttle actuator, a brakeactuator, and a steering actuator. For example, the throttle actuatorcontrols, in accordance with a control signal output from the ECU 150,an amount by which to open the throttle of HEV 100 to control a drivingforce (the engine) of HEV 100. In another example, actuators 206 mayinclude one or more of MGs 191 and 192, where a control signal issupplied from the ECU 150 to MGs 191 and/or 192 to output motiveforce/energy. The brake actuator controls, in accordance with a controlsignal output from the ECU 150, the amount of braking force to beapplied to each wheel of the vehicle, for example, by a hydraulic brakesystem. The steering actuator controls, in accordance with a controlsignal output from the ECU 150, driving an assist motor of an electricpower steering system that controls steering torque.

HMI 207 may be an interface used for communicating information between apassenger(s) (including the operator) of HEV 100 and autonomous controlsystem 200. For example, the HMI 207 may include a display panel fordisplaying image information for the passenger(s), a speaker foroutputting audio information, and actuation mechanisms, such as buttonsor a touch panel used by the occupant for performing an input operation.HMI 207 may also or alternatively transmit the information to thepassenger(s) through a mobile information terminal connected wirelesslyand receive the input operation by the passenger(s) through the mobileinformation terminal.

Monitor device 208 monitors a status of the driver/operator. The monitordevice 208 can check a manual driving preparation state of the driver.More specifically, the monitor device 208 can check, for example,whether or not the driver is ready to start manual operation of HEV 100.Moreover, the monitor device 208 can check, for example, whether or notthe driver has some intention of switching HEV 100 to a manual mode ofoperation.

For example, the monitor device 208 may be a camera that can take animage of the driver, where the image can be used for estimating thedegree to which the driver’s eyes are open, the direction of thedriver’s gaze, whether or not the driver is holding the steering wheel,etc. Monitor device 208 may also be a pressure sensor for detecting theamount of pressure the driver’s hand(s) are applying to the steeringwheel. As another example, the monitor device 208 can be a camera thattakes an image of a hand of the driver.

A shift lever 209 can be positioned at a shift position, e.g., “A(AUTOMATIC),” “D (DRIVE),” etc. The shift position “A” indicates, forexample, an automatic engage mode where autonomous control is engagedautomatically. The shift position “D” indicates a triggered engage modewhere autonomous control is engaged in response to a driver-initiatedrequest to operate HEV 100 in an autonomous driving mode.

Auxiliary devices 210 may include devices that can be operated by thedriver of the vehicle, but are not necessarily drive-related, such asactuators 206. For example, auxiliary devices 210 may include adirection indicator, a headlight, a windshield wiper and the like.

ECU 150 may execute autonomous control of the vehicle, and may includean acquisition unit 211, a recognition unit 212, a navigation plangeneration unit 213, a calculation unit 214, a presentation unit 215,and a control unit 216.

Acquisition unit 211 may obtain the following operation amounts orlevels of actuation based on the information obtained by the internalsensor 203: steering operation, acceleration operation, and brakeoperation by the driver during an autonomous control mode; and the levelof steering operation, acceleration operation, and brake operation bythe driver of the vehicle during a manual control mode.

Recognition unit 212 may recognize or assess the environment surroundingor neighboring HEV 100 based on the information obtained by the externalsensor 201, the GPS reception unit 202, and/or the map database 204. Forexample, the recognition unit 212 includes an obstacle recognition unit(not shown), a road width recognition unit (not shown), and a facilityrecognition unit (not shown). The obstacle recognition unit recognizes,based on the information obtained by the external sensor 201, obstaclessurrounding the vehicle. For example, the obstacles recognized by theobstacle recognition unit include moving objects such as pedestrians,other vehicles, motorcycles, and bicycles and stationary objects such asa road lane boundary (white line, yellow line), a curb, a guard rail,poles, a median strip, buildings and trees. The obstacle recognitionunit obtains information regarding a distance between the obstacle andthe vehicle, a position of the obstacle, a direction, a relativevelocity, a relative acceleration of the obstacle with respect to thevehicle, and a category and attribution of the obstacle. The category ofthe obstacle includes a pedestrian, another vehicle, a moving object,and a stationary object. The attribution of the obstacle can refer to aproperty of the obstacle such as hardness and a shape of the obstacle.

The road width recognition unit recognizes, based on the informationobtained by the external sensor 201, the GPS reception unit 202, and/orthe map database 204, a road width of a road in which the vehicle isrunning.

The facility recognition unit recognizes, based on the map informationobtained from the map database 204 and/or the vehicle positioninformation obtained by the GPS reception unit 202, whether or not HEV100 is operating/being driven through an intersection, in a parkingstructure, etc. The facility recognition unit may recognize, based onthe map information and the vehicle position information, whether or notthe vehicle is running in a school zone, near a childcare facility, neara school, or near a park, etc.

Navigation plan generation unit 213 may generate a navigation plan forHEV 100 based on the target route calculated by the navigation system205, the information on obstacles surrounding HEV 100 recognized byrecognition unit 212, and/or the map information obtained from mapdatabase 204. The navigation plan may be reflect one or more operatingconditions/controls to effectuate the target route. For example, thenavigation plan can include a target speed, a target acceleration, atarget deceleration, a target direction, and/or a target steering anglewith which HEV 100 should be operated at any point(s) along the targetroute so that the target route can be achieved to reach a desireddestination. It should be understood that navigation plan generationunit 213 generates the navigation plan such that HEV 100 operates alongthe target route while satisfying one or more criteria and/orconstraints, including, for example, safety constraints, legalcompliance rules, operating (fuel/energy) efficiency, and the like.Moreover, based on the existence of obstacles surrounding HEV 100, thenavigation plan generation unit 213 generates the navigation plan forthe vehicle so as to avoid contact with such obstacles.

Calculation unit 214 may calculate a threshold used for determiningwhether or not to switch from autonomous control to manual driving orvice versa. The determination can be performed based on the operatinglevels associated with the manner in which the driver is operating HEV100 during autonomous control which is obtained by the acquisition unit211. For example, the driver of HEV 100 may suddenly grasp the steeringwheel (which can be sensed by internal sensor 203) and stomp on thebrake pedal (which can be sensed by monitor device 208). The pressure onthe steering wheel and the level of actuation of the brake pedal may beexcessive enough (exceed a threshold) suggesting that the driver intendsto override the autonomous control system 200.

Presentation unit 215 displays, on a display of the HMI 207, a thresholdwhich is calculated by the calculation unit 214 and used for determiningwhether or not to execute the switching from autonomous control to themanual driving or vice versa.

Control unit 216 can autonomously control HEV 100 based on thenavigation plan generated by navigation plan generation unit 213. Thecontrol unit 216 outputs, to the actuators 206, control signalsaccording to the navigation plan. That is, the control unit 216 controlsactuators 206 based on the navigation plan, and thereby autonomouscontrol of HEV 100 is executed/achieved. Moreover, certain levels ofoperation, e.g., steering wheel actuation, by the driver can be detectedby the acquisition unit 211. When such level(s) equal or exceed thethreshold calculated by the calculation unit 214 in a period duringwhich autonomous control is being used to operate HEV 100, control unit216 executes a switching from autonomous control to manual control.

Referring to FIG. 2B, control unit 216 operatively interacts with safetycontrol unit 220 that determines whether or not autonomous controlsystem 200 (in particular, control unit 216) can engage (activate,start) in autonomous control of HEV 100. For example, safety controlunit 220 may include one or more determination units, e.g.,determination unit 222 a determines whether or not autonomous controlcan be engaged, based on a difference between a vehicle positioncalculated from signals received by the GPS reception unit 202 and anactual vehicle position calculated based on an output signal from theexternal sensor 201, the map information of the map database 204 and soforth. For example, a threshold condition associated with engagement ofautonomous control in HEV 100 may be predicated on travel along acertain type of roadway, e.g., known segment(s) of road within mapdatabase 204, such as a freeway (versus) country lane. Road curvaturemay be another condition/characteristic on which autonomous control ofHEV 100 may be based. Determination unit 222 a may make itsdetermination based on one or more determinative factors.

Control unit 216 may further interact with a determination unit 222 b ofsafety control unit 220 that determines whether or not a trigger todeactivate (stop) an autonomous control mode exists. For example,determination unit 222 b can determine whether or not to execute theswitch from the autonomous control to manual control based on the levelof steering wheel actuation, brake pedal actuation, etc. effectuated bythe driver while HEV 100 is being operated in an autonomous controlmode, which is obtained by the acquisition unit 211. Other determinativefactors or considerations may be the amount of acceleration ordeceleration experienced by HEV 100, also determined by acquisition unit211. When determination unit 222 determines that the autonomous controlcan be engaged, based on the determinations performed by determinationunits 222 a and/or 222 b, control unit 216 engages autonomous control ofHEV 100. That is, determination unit 222 may act as a determinationaggregator that aggregates determinations rendered by otherdetermination units. Determination unit 222 may be a circuit, e.g.,application-specific integrated circuit, logic, software, or somecombination thereof that processes the individual determinationsrendered by the other determination units (e.g., determination units 222a and 222 b) to render an overall determination. That overalldetermination may control operation of control unit 216, e.g., todisengage autonomous control and switch to manual control or engage inautonomous control.

On the other hand, when determination units 222 a and/or 222 b determinethat a switch from autonomous control to the manual control should beexecuted, autonomous control is deactivated/disengaged by control unit216 or control unit 216 is itself deactivated/disengaged, and the driverproceeds to manually control HEV 100. It should be understood that otherdetermination units may be used (or only a single determination unit maybe used). In the case of multiple determination units being used, insome embodiments, any single determination that manual control should beexecuted can serve as a trigger to deactivate autonomous control. Insome embodiments, presentation unit 215 is provided with a control statenotification unit 215 a that notifies the driver of a fact that HEV 100is operating under autonomous control is in execution, and so forth.Such a notification may be displayed on a display of HMI 207, forexample. Likewise, If a switch from autonomous control to the manualcontrol is executed, the control state notification unit 215 a displays,on the display of HMI 207 a corresponding notification.

HMI 207, in some embodiments, may include an autonomous controlengagement trigger input unit 207 a that can be actuated by the driverof HEV 100 to engage in an autonomous control mode (after safety controlunit 220 determines that autonomous control can be effectuated).

In some embodiments, the driver of HEV 100 may be able to select anautomatic autonomous control engage mode, where autonomous control unit216 can be automatically engaged when safety control unit 220 determinesthat the autonomous control can be engaged. In some embodiments, shiftlever 209 may be used to set a triggered autonomous control mode and anautomatic engage mode (as alluded to above by actuating shift lever 209to an “A” (AUTOMATIC) position or to a “D” (DRIVE) position.

FIG. 3 illustrates an example embodiment where the ADAS system mayrecommend a feature. The vehicle gathers data about the driver frommultiple sources and sensors. Data may come from sensors located insideand outside the vehicle. These sensors may include, but are not limitedto speed and brake sensors, eye sensors, video cameras, shock sensors,or suspension sensors. Data from these sensors can inform the ADAS aboutvarious characteristics about the driver, including, but not limited to,fatigue, focus, physical movements, and emotional expressions. In oneexample, the ADAS may determine that a driver 300 is fatigued based onrapid eye fluttering 302 measured by the video cameras and/or eyetrackers 304. In another example, a driver may be losing focus becausetheir body and facial movements are not consistently pointed towards theroad. Sensors also measure characteristics of the vehicle and thesurrounding environment. These can include, but are not limited to, lanetracking via video cameras, speed profiles (including acceleration anddeceleration rates), temperature measurements, and monitoring weatherconditions. In FIG. 3 , the weather can be measured by a temperatureand/or light reading 306 to determine that the weather is generallysunny 308. The ADAS also perceives individual events outside of thenormal course of driving. For example, the system may measure thedeceleration of the vehicle and determine that the rate exceeds typicalbraking. Furthermore, the system can pair measured deceleration withdata demonstrating that an object is growing closer to the vehicle. Inthis example, the system can perceive that the vehicle is entering asituation with a risk of collision. These events guide the ADAS towardan appropriate course of action.

Using the events and/or environmental factors, the ADAS determineswhether an ADAS feature would be appropriate, meaning that it wouldimprove the safety or efficiency of driving in a given situation. Forexample, in FIG. 3 , on an open highway with a consistent speed andcooperating weather, the system may note that cruise control would beappropriate. The ADAS also pulls data from the driver’s past trips,including, but not limited to, histories of using certain ADAS features,average speeds, typical braking speeds, and following distance inbetween cars. For example, the system may note that the driver usuallyguides the vehicle to follow another vehicle with fifteen feet of space.This data allows the system to generate a user profile that outlines thedriver’s behavior.

A driver profile can include multiple generalized characteristics aboutthe driver. For example, if a driver is fatigued after four hours ofconstant driving, the ADAS may note that the driver typically growstired after three hours. As another example, the system may note thatthe driver tends to speed more on the highways than on residentialroads. The system may note that the average speeds change depending onthe weather conditions, or note that the driver acts more confidently orrecklessly in inclement weather. As another example, the ADAS may notethat the driver struggles to parallel park, based on the length of timeand the amount of turns necessary to sufficiently park the vehicle. Thesystem can the note that the driver is inexperienced with parallelparking. In another example, the driver may maintain a decelerationprofile to determine that the driver typically brakes with more forcethan the average driver. The system can determine whether the driver isat risk for collisions or merely brakes at a closer distance normally.The driver profile allows the ADAS to tailor the system to an individualdriver’s needs.

These determinations are tied to the driver’s use of ADAS features. Thesystem aims to ease a driver’s experience based on perceiveddifficulties in certain environments. Furthermore, the ADAS determineswhether a driver is unaware about the existence of an ADAS feature basedon the driver behavior. This can be accomplished using machine learningand/or a set of rules. In one example, the system can measure the numberof times an ADAS feature could have been used but was not initiated. Ifthat number exceeds a threshold value, the system can determine that thedriver is unaware of the feature. In another example, the system candetermine that the driver turned off an automatic ADAS feature and chosenot to use it in past trips, or has repeatedly turned off an ADASfeature during situations where the feature would be appropriate. Inanother example, a situation may appear to warrant a collision warning.However, the driver’s behavior indicates that the driver typicallybrakes with more force or at a closer distance from an approachingvehicle. The system can then determine that the driver does not need arecommendation and/or has already chosen not to use a particular ADASfeature. The ADAS is capable of dynamically following a driver’s choicesin order to determine whether a recommendation would be beneficial.

Once the ADAS determines that the driver is unaware about the existenceof a feature, it can produce a prompt that notifies the driver about theADAS features and allows the driver to initiate any or all of thesuggested features. In FIG. 3 , one example of a prompt can be a textmessage on a LED display with a touch screen 310. This display can takethe form of any display, including, but not limited to, a touchscreen,standard dashboard, or a panel of actuation mechanisms (e.g. buttons)with an accompanying display for text. If the ADAS chooses to prompt adriver, the text may say “You seem a little tired, would you like toturn on cruise control?” This text may be accompanied by a shortcut 312that the driver can access via voice control, touchpad, button, oranother actuation mechanism to initiate the suggested ADAS feature. Thedriver may also turn on the ADAS feature based on the standard methodthrough a main console, after which the prompt would disappear. Thisprompt can also appear at various times during a trip. In the aboveexample, the prompt would appear during a trip at the point where theADAS feature would be appropriate. In another example, the prompt mayappear after the driver has parked and turned off the vehicle. Beforeturning off the vehicle, a prompt can be displayed, such as “Did youknow that automatic braking is turned off? Would you like to turn iton?” The ADAS may even retrieve video information to show the driverspecifically when an ADAS feature could have been used during theprevious trip. Ultimately, the priority for the ADAS proactivelyincreases driver safety before a hazardous event.

The ADAS may even store information about the driver’s behavior to sendto a third party. For example, if a minor drives the vehicle, the ADAScan send information to parents if a certain event occurs or as ageneral update on the minor’s driving. This information can be sentthrough an online account or through an online mailing system. If acollision occurs, the parents would be able to see exactly how thecollision happened. Similarly, information could be sent to fleetmanagers for a company if the company’s driver acts inappropriatelyduring an event. The fleet managers could view video footage if the ADASdetects that a driver is intoxicated or fatigued. This information canbe sent during the trip as an event occurs or at the end of the businessday once a driver has made all necessary stops. The third partyreceiving this information may receive a summary of the events thatoccurred during the day, or a list of significant events that are causefor concern. The third party can specify their informational needs andthe ADAS can filter the driver’s history accordingly.

FIG. 4 is a flow chart illustrating example operations that may beperformed to recommend the ADAS feature. The system obtains sensor data400 from the vehicle to determine a particular event as well as theconditions surrounding that event for the driver and the vehicle. Asdiscussed above, the sensor data 400 is pooled with the driver’s pastinteraction data 402 to correlate the driver’s behavior to a particularevent. The system can generally determine the user behavior 404 as wellas determine a predicted behavior for a specific event similar or equalto the current driving situation. The system can then perceive thecurrent driving event and determine one or more ADAS features that wouldbe appropriate for the event. This determination is made in line withdata on previous drivers and data from the driver’s past interactions.The system then determines whether the ADAS feature should berecommended to the driver. As discussed above, the system may determinethat the driver is unlikely to use the ADAS feature, referring to thedriver’s tendency to turn off the ADAS feature or based on othercharacteristics of the driver’s behavior. Alternatively, the system maydetermine that while similar to an event where an ADAS feature would beappropriate, for the particular driver or situation, the ADAS featurewould not be appropriate. For example, on a highway, cruise control maybe appropriate. However, if the particular event includes heavy rain,and the driver’s behavior reflects difficulty driving in the rain,cruise control may not be appropriate for the particular driver. In anyof the above cases, the ADAS may choose to remain silent and notrecommend the ADAS feature.

In contrast, the system may determine that an ADAS feature should berecommended. This can be one or more ADAS features, with each ADASfeature deriving from an individual analysis that the ADAS feature wouldbe appropriate for the situation. As discussed above, a recommendationcan occur because the driver is unaware of an ADAS feature. Arecommendation can also occur because the system determined that thedriver is likely to accept the prompt. Each ADAS feature to berecommended can be associated with one or more prompts that can bedisplayed to the driver. For example, a prompt can be designated forcruise control on an open highway and a separate prompt can bedesignated for cruise control during inclement weather. As anotherexample, a prompt can be associated with beeping when a driver makes adangerous left turn across traffic. A second prompt can be associatedwhen the left turn is instead associated with an illegal U-turn. As thedriver responds to the prompts, the system can continue to be trained toadopt to the specific driver’s needs. If multiple drivers use thevehicle, separate models can be maintained for each driver, and eachprompt will train the specific model.

As used herein, the terms circuit and component might describe a givenunit of functionality that can be performed in accordance with one ormore embodiments of the present application. As used herein, a componentmight be implemented utilizing any form of hardware, software, or acombination thereof. For example, one or more processors, controllers,ASICs, PLAs, PALs, CPLDs, FPGAs, logical components, software routinesor other mechanisms might be implemented to make up a component. Variouscomponents described herein may be implemented as discrete components ordescribed functions and features can be shared in part or in total amongone or more components. In other words, as would be apparent to one ofordinary skill in the art after reading this description, the variousfeatures and functionality described herein may be implemented in anygiven application. They can be implemented in one or more separate orshared components in various combinations and permutations. Althoughvarious features or functional elements may be individually described orclaimed as separate components, it should be understood that thesefeatures/functionality can be shared among one or more common softwareand hardware elements. Such a description shall not require or implythat separate hardware or software components are used to implement suchfeatures or functionality.

Where components are implemented in whole or in part using software,these software elements can be implemented to operate with a computingor processing component capable of carrying out the functionalitydescribed with respect thereto. One such example computing component isshown in FIG. 5 . Various embodiments are described in terms of thisexample-computing component 500. After reading this description, it willbecome apparent to a person skilled in the relevant art how to implementthe application using other computing components or architectures.

Referring now to FIG. 5 , computing component 500 may represent, forexample, computing or processing capabilities found within aself-adjusting display, desktop, laptop, notebook, and tablet computers.They may be found in hand-held computing devices (tablets, PDA’s, smartphones, cell phones, palmtops, etc.). They may be found in workstationsor other devices with displays, servers, or any other type ofspecial-purpose or general-purpose computing devices as may be desirableor appropriate for a given application or environment. Computingcomponent 500 might also represent computing capabilities embeddedwithin or otherwise available to a given device. For example, acomputing component might be found in other electronic devices such as,for example, portable computing devices, and other electronic devicesthat might include some form of processing capability.

Computing component 500 might include, for example, one or moreprocessors, controllers, control components, or other processingdevices. This can include a processor 504. Processor 504 might beimplemented using a general-purpose or special-purpose processing enginesuch as, for example, a microprocessor, controller, or other controllogic. Processor 504 may be connected to a bus 502. However, anycommunication medium can be used to facilitate interaction with othercomponents of computing component 500 or to communicate externally.

Computing component 500 might also include one or more memorycomponents, simply referred to herein as main memory 508. For example,random access memory (RAM) or other dynamic memory, might be used forstoring information and instructions to be executed by processor 504.Main memory 508 might also be used for storing temporary variables orother intermediate information during execution of instructions to beexecuted by processor 504. Computing component 500 might likewiseinclude a read only memory (“ROM”) or other static storage devicecoupled to bus 502 for storing static information and instructions forprocessor 504.

The computing component 500 might also include one or more various formsof information storage mechanism 510, which might include, for example,a media drive 512 and a storage unit interface 520. The media drive 512might include a drive or other mechanism to support fixed or removablestorage media 514. For example, a hard disk drive, a solid-state drive,a magnetic tape drive, an optical drive, a compact disc (CD) or digitalvideo disc (DVD) drive (R or RW), or other removable or fixed mediadrive might be provided. Storage media 514 might include, for example, ahard disk, an integrated circuit assembly, magnetic tape, cartridge,optical disk, a CD or DVD. Storage media 514 may be any other fixed orremovable medium that is read by, written to or accessed by media drive512. As these examples illustrate, the storage media 514 can include acomputer usable storage medium having stored therein computer softwareor data.

In alternative embodiments, information storage mechanism 510 mightinclude other similar instrumentalities for allowing computer programsor other instructions or data to be loaded into computing component 500.Such instrumentalities might include, for example, a fixed or removablestorage unit 522 and an interface 520. Examples of such storage units522 and interfaces 520 can include a program cartridge and cartridgeinterface, a removable memory (for example, a flash memory or otherremovable memory component) and memory slot. Other examples may includea PCMCIA slot and card, and other fixed or removable storage units 522and interfaces 520 that allow software and data to be transferred fromstorage unit 522 to computing component 500.

Computing component 500 might also include a communications interface524. Communications interface 524 might be used to allow software anddata to be transferred between computing component 500 and externaldevices. Examples of communications interface 524 might include a modemor softmodem, a network interface (such as Ethernet, network interfacecard, IEEE 802.XX or other interface). Other examples include acommunications port (such as for example, a USB port, IR port, RS232port Bluetooth® interface, or other port), or other communicationsinterface. Software/data transferred via communications interface 524may be carried on signals, which can be electronic, electromagnetic(which includes optical) or other signals capable of being exchanged bya given communications interface 524. These signals might be provided tocommunications interface 524 via a channel 528. Channel 528 might carrysignals and might be implemented using a wired or wireless communicationmedium. Some examples of a channel might include a phone line, acellular link, an RF link, an optical link, a network interface, a localor wide area network, and other wired or wireless communicationschannels.

In this document, the terms “computer program medium” and “computerusable medium” are used to generally refer to transitory ornon-transitory media. Such media may be, e.g., memory 508, storage unit520, media 514, and channel 528. These and other various forms ofcomputer program media or computer usable media may be involved incarrying one or more sequences of one or more instructions to aprocessing device for execution. Such instructions embodied on themedium, are generally referred to as “computer program code” or a“computer program product” (which may be grouped in the form of computerprograms or other groupings). When executed, such instructions mightenable the computing component 500 to perform features or functions ofthe present application as discussed herein.

It should be understood that the various features, aspects andfunctionality described in one or more of the individual embodiments arenot limited in their applicability to the particular embodiment withwhich they are described. Instead, they can be applied, alone or invarious combinations, to one or more other embodiments, whether or notsuch embodiments are described and whether or not such features arepresented as being a part of a described embodiment. Thus, the breadthand scope of the present application should not be limited by any of theabove-described exemplary embodiments.

Terms and phrases used in this document, and variations thereof, unlessotherwise expressly stated, should be construed as open ended as opposedto limiting. As examples of the foregoing, the term “including” shouldbe read as meaning “including, without limitation” or the like. The term“example” is used to provide exemplary instances of the item indiscussion, not an exhaustive or limiting list thereof. The terms “a” or“an” should be read as meaning “at least one,” “one or more” or thelike; and adjectives such as “conventional,” “traditional,” “normal,”“standard,” “known.” Terms of similar meaning should not be construed aslimiting the item described to a given time period or to an itemavailable as of a given time. Instead, they should be read to encompassconventional, traditional, normal, or standard technologies that may beavailable or known now or at any time in the future. Where this documentrefers to technologies that would be apparent or known to one ofordinary skill in the art, such technologies encompass those apparent orknown to the skilled artisan now or at any time in the future.

The presence of broadening words and phrases such as “one or more,” “atleast,” “but not limited to” or other like phrases in some instancesshall not be read to mean that the narrower case is intended or requiredin instances where such broadening phrases may be absent. The use of theterm “component” does not imply that the aspects or functionalitydescribed or claimed as part of the component are all configured in acommon package. Indeed, any or all of the various aspects of acomponent, whether control logic or other components, can be combined ina single package or separately maintained and can further be distributedin multiple groupings or packages or across multiple locations.

Additionally, the various embodiments set forth herein are described interms of exemplary block diagrams, flow charts and other illustrations.As will become apparent to one of ordinary skill in the art afterreading this document, the illustrated embodiments and their variousalternatives can be implemented without confinement to the illustratedexamples. For example, block diagrams and their accompanying descriptionshould not be construed as mandating a particular architecture orconfiguration.

What is claimed is:
 1. A method for effectuating an advanced driver-assistance system (ADAS) of a vehicle comprising: obtaining sensor data from one or more sensors; retrieving data regarding a user’s past interactions with the ADAS; determining the user’s behavior based on the sensor data and the data regarding the user’s past interactions; and adjusting the ADAS in response to the user’s behavior.
 2. The method of claim 1, further comprising determining whether the user is unaware of the existence of an ADAS feature based on the user’s behavior and recommending the ADAS feature to the user if the user is determined to be unaware.
 3. The method of claim 1, wherein adjusting the ADAS comprises determining whether an ADAS feature is applicable to a situation and recommending the ADAS feature to the user.
 4. The method of claim 1, wherein the data on the user’s past interactions includes information of each of turn on operations of the ADAS and turn off operations of the ADAS.
 5. The method of claim 3, wherein recommending the ADAS feature includes providing a prompt to initiate the ADAS feature and initiating the ADAS feature.
 6. The method of claim 5, wherein providing the prompt is completed with a LED display and the LED display provides a shortcut to turn on the recommended ADAS feature.
 7. The method of claim 1, further comprising determining when the user turned off an ADAS feature; determining whether the ADAS feature was subsequently updated; and notifying the user about the updated ADAS feature.
 8. The method of claim 1, wherein the user behavior reflects the past interactions of a first user, and further comprising sharing the user behavior with a second user.
 9. The method of claim 1, wherein the sensor data includes the user’s facial and physical expressions.
 10. The method of claim 1, wherein the past user interaction data includes previous recommendations on ADAS features that the user ignored.
 11. The method of claim 1, wherein the past user interaction data includes the number of times an ADAS feature was turned off.
 12. A vehicle, comprising: a processor; a plurality of sensors; and a memory unit operatively connected to the processor and including computer code, that when executed, causes the processor to: obtain sensor data from the plurality of sensors; retrieve data on a user’s past interactions; determine the user’s behavior based on the sensor data and data on past user interactions; determine whether the user is unaware of an ADAS feature; recommend the ADAS feature to the user on a display by presenting, on the display, a prompt to initiate the ADAS feature; and adjust the ADAS according to the user’s response.
 13. The vehicle of claim 12, wherein the prompt is a textual message and further comprises an actuation mechanism to initiate the ADAS feature and an actuation mechanism to ignore the prompt.
 14. The vehicle of claim 12, wherein the memory unit includes computer code, that when executed, further causes the processor to determine whether an ADAS feature is applicable to a situation.
 15. The vehicle of claim 12, wherein the data on the user’s past interactions includes information of each of turn on operations of the ADAS and turn off operations of the ADAS.
 16. The vehicle of claim 12, wherein the user’s behavior reflects the past interactions of a first user, and wherein the memory unit includes computer code, that when executed, further causes the processor to share the user behavior with a second user.
 17. The vehicle of claim 12, wherein the past user interaction data includes previous recommendations on ADAS features that the user ignored and wherein the memory unit includes computer code, that when executed, further causes the processor to abstain from recommending an ADAS feature if the user previously ignored a recommendation.
 18. The vehicle of claim 12, wherein the past user interaction data includes the number of times an ADAS feature was turned off and wherein the memory unit includes computer code, that when executed, further causes the processor to abstain from recommending an ADAS feature if the ADAS feature was turned off one or more times.
 19. The vehicle of claim 12, wherein the one or more sensors includes at least one of an eye tracking sensor, speed sensor, facial recognition sensor, and environmental sensor.
 20. The vehicle of claim 12, wherein the display is a LED display. 